Welcome to the Instructable for the DIY BackpAQ Personal Air Quality Monitor V3! As we did in the Instructable for BackpAQ Version 2, we will build a high-quality instrument capable of measuring and monitoring the most common sources of air pollution, both indoors and outdoor, including particulate matter (PM1, PM2.5, PM10) gases (TVOC, CO2), along with temperature and relative humidity. New for V3 will be inclusion of a sound sensor for identifying and monitoring noise pollution. An upgraded CO2 sensor is also included in the V3 build. Let's take a look!

Step 1: The BackpAQ Project, What We'll Build, What We'll Learn

The BackpAQ Project

The BackpAQ project is part of a middle and high school STEM curriculum that promotes learning about and experience with the monitoring of air quality (AQ) particularly in disadvantaged communities, and drives engagement among underrepresented youth in STEM activities. Key to the program is deployment of a suite of community-based mobile air quality monitors that leverage new low-cost sensors. These handheld units can be readily assembled by advanced middle-school and high school students and other STEM-oriented youth who are motivated by interest in obtaining, understanding and sharing hyper-local air quality data.

What we'll build

For this project we are going to build a BackpAQ V3 personal air quality (AQ) monitor. As you can see from the accompanying photos, BackpAQ is designed to be easily carried, clipped to a backpack, or placed in a mobile scenario such as a vehicle or other transport. As BackpAQ utilizes GPS positioning technology, the AQ information we collect will be geo-positioned no matter where the monitor goes. These student-built monitors, encased in a lightweight polycarbonate box, weigh less than a pound and are powered by rechargeable LiPo batteries. They feature carabineers and nylon straps for easy fastening to a backpack or bicycle frame.

What we’ll measure

As designed, the monitors will measure and display criteria pollutants PM1, PM2.5, and PM10 concentrations in ug/m3, as well as display the US EPA Air Quality Index (AQI). Gases such as TVOC and CO2 are also easily monitored with BackpAQ. Monitoring of additional pollutants, such as CO, O3, NO2 and SO2 are possible future enhancements. V3 add a tiny MEMS-based microphone so that sound can be captured. More about this in an upcoming section.

The latest version pairs with a companion smartphone app to provide an interactive user experience and allow customization and personalization of monitored data and how it’s displayed. BackpAQ automatically uploads data to the Thingspeak cloud where it can be visualized using powerful analytics, and shared with other students or local community officials.

What we'll learn

To begin with, we'll learn design, build and fabrication techniques - along with some pretty powerful electronics, Internet-of-Things (IOT), and sensor technology skills. Perhaps most importantly, we'll learn how to curate and analyze data we capture from the monitors. Learning how to develop and apply critical judgement to the data and subsequent reporting and sharing of findings and implications are key outcomes of this project.

Outcomes

The intended outcome of this project is twofold: one, obtain a richer, deeper understanding of air pollution, where it comes from, how to measure it, how to harness powerful analytics to responsibly report and share findings, and (hopefully) gain some insight that will enable ordinary concerned people to do something about it. And two, build a monitoring device - BackpAQ - to better understand the science and engineering behind sensors, IOT, the Maker Movement, and have hands-on involvement with one of the more critical challenges facing communities today.

Step 2: How This Instructable Is Organized

The BackpAQ Instructable is organized as follows:

Introduction

Air Pollution and What We're Measuring

Design Point

Overview of the Project

Materials

The Build

Software and Cloud

Futures

Although we've laid out a sequential learn + build process, feel free to skip around or just jump to a specific Step. For example, you may wish to set up the software first before diving into the BackpAQ device. Your choice...have fun!

Step 3: What We'll Measure

Particulates

Before we get started building, let's take a look at the science behind air quality, sensors and monitoring. So what are "Particulates" (PM), and how do they get into the air?

Size comparisons for PM particles

PM stands for particulate matter (also called particle pollution): the term for a mixture of solid particles and liquid droplets found in the air. Some particles, such as dust, dirt, soot, or smoke, are large or dark enough to be seen with the naked eye. Others are so small they can only be detected using an electron microscope. Particle pollution includes: PM10 : inhalable particles, with diameters that are generally 10 micrometers and smaller; and PM2.5 : fine inhalable particles, with diameters that are generally 2.5 micrometers and smaller. How small is 2.5 micrometers? Think about a single hair from your head. The average human hair is about 70 micrometers in diameter – making it 30 times larger than the largest fine particle.

Sources of PM

These particles come in many sizes and shapes and can be made up of hundreds of different chemicals. Some are emitted directly from a source, such as construction sites, unpaved roads, fields, smokestacks or fires. Most particles form in the atmosphere as a result of complex reactions of chemicals such as sulfur dioxide and nitrogen oxides, which are pollutants emitted from power plants, industries and automobiles.

What are the Harmful Effects of PM?

Particulate matter contains microscopic solids or liquid droplets that are so small that they can be inhaled and cause serious health problems. Some particles less than 10 micrometers in diameter can get deep into your lungs and some may even get into your bloodstream. Of these, particles less than 2.5 micrometers in diameter, also known as fine particles or PM2.5, pose the greatest risk to health. Fine particles are also the main cause of reduced visibility (haze) in parts of the United States, including many of our treasured national parks and wilderness areas.

The PM Sensor for BackpAQ

The particulate sensor we have chosen for this project is the Plantower PMS7003. It is able to measure the concentration of fine particles of less than 1μm (PM1); less than 2.5μm (PM2.5) and less than 10μm (PM10). The operating principle of the PMS7003 sensor is as follows: a laser illuminates airborne particles. An optical sensor captures the laser light and generates an electrical signal proportional to the rate and size of the particles in the air. This block diagram shows what's going on inside the sensor. Note that there is a microprocessor built-in that does some computation and digitization of the signal so that we can read the data in our own hardware.

What are ATM and CF1?

The CF_ATM and CF_1 values are calculated from the particle count data with a proprietary algorithm developed by the PMS7003 laser counter manufacturer, Plantower. The specifics of the calculation are not available to the public (or us for that matter). However, to convert the particle count data (um/dl) to a mass concentration (ug/m3) they must use an average particle density. They do provide 2 different mass concentration conversion options; CF_1 uses the "average particle density" for indoor particulate matter and CF_ATM uses the "average particle density" for outdoor particulate matter. Depending on the density of the particles you are measuring the sensor could appear to read "high" or "low". Some groups have developed conversion factors to convert the data from the sensor to match the unique average particle density within their airshed.

Measuring CO2

Carbon dioxide is a gas heavier than air. In small quantities of up to 5000ppm (0.5% ) can cause headaches, lethargy, slowing of intellectual ability, irritability, sleep disturbance. In larger quantities can cause dizziness, loss of sight, hearing or knowledge. Typically, fresh air contains between 360ppm and 410 ppm of CO2. What are the benefits of monitoring CO2 levels? When a group of people are indoors, the concentration of CO2 is expected to increase, as humans naturally exhale CO2. However, at high concentrations, humans can experience negative effects, including reduced concentration and a compromised well-being. CO2 sensors like the SCD4x serve to measure and control elevated CO2 concentrations to counteract these negative symptoms. Studies have shown positive effects on productivity and health when CO2 concentrations in an environment are below 1000 ppm. Comparatively, the normal CO2 level for outdoor environments is at around 400 ppm. CO2 sensors can be used to maintain optimal CO2 levels indoors, as their measurements can be used to monitor levels and act accordingly by bringing in fresh air via mechanical ventilation (Demand Controlled Ventilation (DVC), air handling units, etc.) or natural ventilation (open doors or windows).

Indoor levels of CO2 concentration and its effect on well-being

Additionally, studies have shown that high indoor CO2 concentrations have an impact on cognitive and work performance (see figure below). In a specific test case, individuals that were taking an exam in a room with high CO2 levels of around 2500 ppm generally performed worse and scored lower than when exposed to a CO2environment at 1000 ppm (Source: NY Times). Moreover, in tighter office spaces like conference rooms, high CO2levels are often heightened, resulting in a negative impact on human productivity and decision making.

What are TVOCs?

VOCs, or volatile organic compounds, are a group of thousands of organic chemicals that evaporate at low temperatures. So, TVOC is just “total volatile organic compounds”, right? It’s “all the VOCs added up together.” Unfortunately, the answer isn’t quite that simple. Most pollutants are extremely easy to define - ozone is three oxygen atoms. SO2 is a molecule composed of one sulfur atom and two oxygen atoms. Even particulate matter, with all its different flavors can be defined in one simple phrase (particulate matter with an aerodynamic diameter less than 2.5µm). But what exactly is TVOC? Wikipedia dedicates an entire subsection JUST to the definition of TVOC. The simple answer is that there is no consensus around how TVOC should be defined. There are literally thousands of VOCs, and countless national bodies, governments and organizations have created their own lists of VOCs to be included in their TVOC definition. Luckily, several standards have emerged based upon research on the VOCs typically found in indoor environments. For example, ISO 16000-29 defines a “VOC mixed gas” comprised of 40 individual compounds. This is a standardized gas mixture used to simulate typical indoor air. Mølhave et al. defines a “Typical IAQ Mix” of 22 VOCs at concentrations similar to those determined on average in residential indoor environments.

How is TVOC measured?

There are a number of ways to measure VOCs, with pros and cons based on the situation, budget available, etc. Historically, laboratory techniques such as flame ionization detectors or gas chromatography–mass spectrometry were used, providing an accurate way to identify specific gases within a sample. While lab-based measurements may be highly accurate, they are unable to provide a continuous measurement of TVOC, which is incredibly important and, some may even argue, more important than having a perfectly accurate value for a specific gas. For BackpAQ, our sensor employs a thin film of metal-oxide nanoparticles. This film is heated to around 300’C (hence the warm up period after turning on a BackpAQ device). During operation, oxygen particles will be adsorbed on the surface, and these in turn will react with the target gas. This reaction causes a release of electrons from the oxygen present on the surface, which in turn leads to a change in electrical resistance of the metal-oxide layer. Chemical reactions within the MOS sensor creates a change in electrical resistance. What the sensor is actually measuring is the electrical resistance of this metal-oxide layer. This real time measurement and output of resistance is the first step in obtaining our TVOC reading. Finally, it's important to remember that the sensor we use will be sensitive to a wide variety of VOCs, rather than to one specific individual VOC.

Measuring Sound and Noise Pollution

Sound travels as pressure fluctuations in the air, in the form of waves of measurable frequency and amplitude. Noise is often defined as unwanted or unpleasant sound.

Exposure to noise at home, at work, or during sleep has been associated with many adverse health and emotional outcomes. These include distraction, annoyance, cardiovascular disease, tinnitus and hearing loss. The World Health Organization states that traffic noise alone is harmful to the health of almost every third person in Europe, and that one in five Europeans is regularly exposed to sound levels at night that could significantly damage health.

The MEMS chip we use has a high-performance digital microphone to detect frequencies between 50 Hz and 8000 Hz, covering the dominant range of human hearing.

Sound Pressure Level (A-weighted)

The Sound Pressure Level (SPL) is a popular measurement system for noise. Sound amplitudes measured by a microphone are averaged over all frequencies to produce a single SPL number, expressed on a logarithmic scale in decibel units. SPL measurements are best for ongoing constant noise, while peak amplitude measurements are best for brief, sudden sounds.

When calculating SPL, some frequencies can be emphasized relative to others – this is known as the weighting. The most common method is “A-weighting”, an internationally recognized standard which accounts for the variation in how the human ear hears different sound frequencies. For example, people’s perception of loudness tends to peak at around 3 kHz and drops at low and high frequencies. Noise around 3 kHz is therefore given a greater weighting when calculating the SPL – this weighting is shown in Figure 7.

The A-weighted Sound Pressure Level is a useful and very commonly used measure of environment noise and sound “loudness”. Table 4 and Table 5 give some example sound sources and typical SPL values. Note that the sound level (perceived or measured) generally depends on:

What is creating the sound
Distance from the source to the meter or ear
Direction, angle or alignment
Other factors such as nearby objects, air conditions, etc.

Table 4 - Typical A-weighted Sound Pressure Level values. All values are approximate and will vary depending on exact source type and positioning.

Table 5 - A-weighted Sound Pressure Level approximate guidelines from the World Health Organization and US government agencies NIOSH and OSHA.

WARNING: these values are not safety advice and should not be treated as such. The sensor product is not suitable for safety or health-critical measurements.

Figure 7 - The standard A-weighting curve.

Frequency band Sound Pressure Level

The MS430 also provides the unweighted SPL for several ranges of sound frequency (known as frequency bands). This reveals what pitches are present in the sound, for example the treble and bass notes in music. The band frequency ranges are listed in Table 6.

Table 6 - Frequency bands for unweighted Sound Pressure Level measurement.

Peak sound amplitude

The peak sound amplitude is a measurement of the largest pressure fluctuation to occur since the last time the value was read. The MS430 continually monitors the sound amplitude and internally updates this peak value (rather than making a one-off measurement). This means that sudden, impulsive noises are not missed. The peak value automatically resets after being read.

The sound interrupt system (explained further in the device datasheet) uses the peak amplitude value as a trigger for a digital output signal. This can be used to respond rapidly to changes in sound level, without the need for software processing.

Ideas for further investigation of sound

Road/aircraft traffic noise – what levels are reached and which times of the day are worst?
Use of sound interrupts for control of appliances e.g. turn on light with specific sequence of hand claps.
Is your home music system set at an appropriate volume?
Are areas for work or study maintained at a low enough sound level?
Test the effectiveness of sound-proofing methods for reducing noise in the home from external sources.
Use the frequency band SPL values to display a frequency spectrum for live visualization of music.

An Important Caveat

The data the Plantower (and other optical counters) produce is an estimation of particulate mass concentration that relies on several assumptions for shape, diameter and density. The quality of your data will depend on those assumptions as well as environmental considerations such as humidity, light and temperature.Because of the fact that optical counters rely on these assumptions, the data produced by them are not FRM or FEM certified.

Step 4: Why Mobile Monitoring?

So Why a mobile monitor?

At this point you might be asking yourself (or your teacher) why are we going to the trouble of building an inexpensive, battery-powered mobile monitor when perfectly good fixed monitors can be had for about the same outlay? Well, here's a bit about why:

Mobile monitoring can thought of as a preliminary step of any air pollution field study design because it enables preliminary exploration of fine-scale spatial variability within a neighborhood, providing confidence in placement of stationary air monitors. Several characteristics of mobile monitoring facilitate its utility as a tool for understanding complex conditions, and, if carefully designed, for disentangling some aspects of temporal and spatial variation.

First, mobile monitoring is cost-effective; the route can be customized to focus on particular areas of concern, such as high traffic roads or neighborhood fixed sources.

Second, concentrations are typically measured at short intervals using continuous instruments which, with good quality-control efforts, can provide information about short-term peak exposures associated with adverse acute health effects. Therefore, through carefully repeating time- and location-specific measures, this technique can provide some stability in determining PM concentrations.

Third, mobile monitoring can also be used to validate conceptual dispersion models by capturing data at multiple points downwind of the source, under varying wind speed and direction conditions.

Finally, leveraging the repeated measures and integrating meteorology and land use characteristics, mobile monitoring data can be used to more richly characterize spatial variability throughout the region, by more knowledgeably tailoring the spatial and temporal characteristics of a fixed-site monitoring network. So that's why.

Beyond this, mobile monitoring enables hyper-local sampling of air quality wherever you go, throughout your neighborhood, community, school, or workplace.

Step 5: Design Characteristics

BackpAQ Design Point

Personal, portable air quality monitoring
Inexpensive to build, operate
Access and control through comprehensive smartphone app
Easily manage data, save & share measurements on the cloud
Measure most common pollutants, including PM2.5, CO2, VOC and sound
User-managed data privacy controls
Access to powerful Cloud-based data management and analytics
Battery powered, rechargeable, solar power option
Over-the-air software update capability (coming soon)

BackpAQ V2 Characteristics

Size: 5" x 2" x 4"
Weight: 10 OZ
Case Material: Polycarbonate
Measured particles: PM1, PM2.5 and PM10
TVOC, CO2 sensors for indoor air quality measurement
MEMS microphone for sound level measurement
Advanced Heltec ESP32 MCU processor, 240Mhz, with built-in OLED display and LiPO charging
Battery Life: around 10-12 hours
Lithium-ion battery: 3v7 - 2500 mAh
2.1mm connector for charging
SD Card Storage (optional)
Sampling period: adjustable 5 - 60 minutes
Multicolored OLED interface for local data display and control
Smartphone Interface (Android, iOS) via Wifi and Blynk
Powerful analytics back-end with ThingSpeak/MatLab
Regular OTA software updates (coming soon)

Step 6: Technical Overview

Technical Overview

The BackpAQ project is constructed from a rich combination of hardware, software and cloud. In building BackpAQ, the student will utilize a full stack, with Arduino-based IDE (C++), a handful of powerful APIs and data abstractions, two advanced environmental sensors, and a powerful cloud capability.

Here's a quick rundown of the basic components.

Processor: 240Mhz Heltec ESP32 microcontroller (MCU) with built-in .96" OLED display
PM Sensor: Plantower PMS7003 laser particle
TVOC Sensor: Sensirion SGP-30
CO2 Sensor: Sensirion SCD-41 photo-acoustic
Temperature/Humidity Sensor: built in to CO2 sensor
MEMS Microphone: Adafruit SPH-0645 or similar
Development Platform: Arduino IDE with simplified C++ programming
Data Storage/Cloud: Thingspeak (Matlab) via well-documented APIs
IOS or Android Smartphone App via Blynk

The heart of BackpAQ V2 is the Heltec ESP32 MCU. The WiFi-based ESP communicates with the PMS7003 sensor via the I2C bus. A small microcontroller inside the sensor transmits the particle concentration values and the number of particles. For TVOC and CO2, same thing happens for the SGP-30 and SCD41 sensors, respectively. The BackpAQ firmware continuously reads the data stream, and sends the calculated values to the local OLED display, and to both the connected smartphone and the ThingSpeak cloud. BackpAQ also calculates AQI, the Air Quality Index. AQI is an index for reporting daily air quality. It tells you how clean or polluted your air is, and what associated health effects might be a concern for you.

The software also continuously measures the battery voltage. If it is below its limit voltage (3v2 = 0%), the device goes into standby. The battery is 100% when the voltage is 4.2V and is visually indicated on the companion smartphone app. The companion smartphone app is really the control center of BackpAQ. Through the app, you can monitor all functions and display virtually any data collected or computed by the device. There are also mapping and reporting capabilities that will help you get the most out of your portable AQ monitoring device. And to get the most out of BackpAQ you'll need a companion smartphone. Currently BackpAQ (and underlying Blynk app) require IOS 9.0 or higher or Android 4.2 or higher.

Step 7: Design and Component Choices

Before we delve into the construction of our BackpAQ, let's review what key decisions and choices we must make in order to fulfill the design characteristics we just talked about.

Choice of PM Sensor

In the past few years a new generation of low-cost sensors has become available. Several of these have been the subject of some prominent evaluations, most recently from AQMD. As noted there and elsewhere, these sensors are generally more suitable for deployment in large numbers in terms of their cost but their precision and accuracy may not be sufficient for regulatory use. Based on our own evaluation, though, one of these would suffice for the usage scenarios we envision for BackpAQ. In this recent study four PM sensors were compared: Plantower PMS5003, Plantower PMS7003, Honeywell HPMA115S040 and Alphasense OPC-N241. The table above lists their main characteristics. These sensors were incorporated into an evaluation breadboard for testing; and they are sufficiently small to be deployed in an enclosure small enough for mobile or wearable applications. They all report PM2.5 and PM10 concentrations in μg/m3. The Plantower PMS5003, the Plantower PMS7003 and the Alphasense OPC-N2 also report PM1 and particle count for different bin sizes - the Plantowers report size distribution for 0.3, 0.5, 1.0, 2.5, 5.0, 10 μm bins and the Alphasense OPC-N2 reports 16 bins ranging from 0.38 μm and17 μm. The Plantower sensors claim a counting efficiency of 98% for particles of diameter 0.5 μm and 50% for diameter 0.3 μm38. All use a sampling interval <10 s. According to the manufacturers, their accuracy is between ±10–15 μg/m3. In reviewing these studies and others, we observed that the PMS5003/7003 received strong ratings in terms of accuracy, precision, and data recovery while also being price-appropriate for this type of instrument (see PurpleAir Evaluation Summary for details.) The Alphasense, at $450, was not appropriate for this project. The Honeywell, though low-cost, did not do particle counts. So that pretty much left the two Plantowers. At BackpAQ Labs we also looked briefly at the Shinyei PPD42NS, Samyoung DSM501A and Sharp GP2Y1010AU0F sensors. Although these were much lower cost, their lack of digital output (in most modes) was a disqualifying factor for our design (electronics must sample the analog output and convert o digital form for the MCU.) Ultimately we chose the PMS-7003 for performance, form factor, low cost and support among developers.

Choice of Microcontroller

This is obviously at the core of BackpAQ V2 and is perhaps the most important design choice. We looked at several options here, including Arduino-compatible MCUs such as Adafruit Feather, ESP32, NodeMCU, and WeMos D1. The ESP32 base was chosen for the second generation device based mainly on processor power, tight WiFi/Bluetooth integration and sufficiently low-power consumption.

The ESP32 is a tiny, relatively inexpensive module with a dual-core 32-bit CPU Controller. The ESP32 is the ESP8266 successor loaded with lots of new features. The version we close - Heltec ESP32 WiFiKit - is a development board that combines Wi-Fi and Bluetooth wireless capabilities, and it’s dual-core. It supports a wide variety of peripherals such as capacitive touch, ADC, DAC, I2C, SPI, UART, I2S, PWM, and much more. It is one of the best solutions for DIY Internet of Things Projects and Smart Home Projects.

Performance was virtually identical with all of these units and choice ultimately came down to footprint and ease of build and interconnection (QWIIC) with sensors and other components. Ultimately, we chose a development board based around the ESP32, a Heltec MCU we have used in previous projects and know to be dependable and quite inexpensive (as low as $15 from several Amazon suppliers). As the design evolves we will revisit this choice and re-evaluate best fit.

Choice of CO2 Sensor

We are using the Sensirion SCD4x Miniaturized CO2 Sensors which sense CO2 and RH/T and fit in a space of just one cubic centimeter. These CO2 sensors offer a 2.4V to 5.5V supply voltage range, fully calibrated digital I2C output, and ±(30ppm + 3%MV) accuracy rating. Compared to the SCD30, the SCD4x footprint has been miniaturized by a factor of 5, resulting in dimensions of just 10.1mm x 10.1mm x 6.5mm. With the use of photoacoustic sensing principle, the dimensions of the optical cavity are greatly reduced without compromising on sensor performance. The SCD4x series features a quality humidity and temperature sensor that delivers two additional sensor outputs. Sensirion SCD4x Miniaturized CO2 Sensors are ideal for sensing markets such as IoT, automotive, HVAC, appliances, and consumer goods.

Communications Mode

To fulfill the design requirement to be 100% mobile and be able to interact with a smartphone and the Internet, we evaluated several comms scenarios. At the beginning of the project, we looked at (1) Cellular; (2) Bluetooth; and (3) WiFi. As was expected, and based on our previous experience with sensor projects, each mode of communications brings advantages and tradeoffs. So we build prototypes to evaluate all three. Cellular, which was arguably the most portable and scalable, cost the most and was the most power hungry. Bluetooth, in particular Bluetooth Low Energy (BLE), was the most flexible and least power intensive. WiFi, with it's wide availability, ease of use, and relatively low power needs, seemed to be the way to go. In the end we chose WiFi, based on it's low power draw, excellent integration with our choice of microcontroller (ESP8266), and near ubiquity across the range of usage scenarios we envision. We may revisit the use of BLE in a future iteration.

Smartphone as Communications Hub

As we've just discussed, WiFi seems the best technology choice for communicating the measurements from the sensors to be stored and obtaining the GPS position of the BackpAQ device. Since the ESP8266 contains networking capabilities in the form of WiFi, it could theoretically perform all tasks of the system but with the prerequisite that an active network connection is available at all times. This would require a local area network or the addition of a GSM modem connecting to a mobile network connection. For location services, another module would be needed to provide GPS support. So..... we need to thoughtfully consider how to inexpensively provide these capabilities. Let's look closer at what is missing. What we need is an active network connection and navigational services for determining our current location. The solution may be right in our pocket! A piece of technology already including both of these features is a regular smartphone which could be used as a gateway between the BackpAQ and network, receiving sensor data and forwarding it. Using a smartphone, much computational work can be moved from the BackpAQ to the phone, also providing the network connection and location services. This means that the ESP8266-powered BackpAQ could be solely responsible for reading sensor data, receiving and acting upon commands and broadcasting data to the phone. The connection between BackpAQ and smartphone can be achieved using WiFi or Bluetooth since both protocols are supported by both devices. Using the network provider of the SIM-card, a connection to online services can be established. In addition to containing the basic features of network capabilities and WiFi/Bluetooth, the phone will also provide GPS in order to give us precise geo-location of the sensors. We'll need this later when we're doing our data analysis, matching AQ to locations.

Battery Monitoring

With any battery-powered device it's critical to be able to monitor power usage, or at least battery voltage. The Heltec ESP32 WiFiKit MCU we are using already has an internal voltage divider that connects the digital pin 37 to an internal voltage divider is made up of 220k (R1) and 100k (R2) resistors. So, by polling this pin we can directly measure the voltage of the battery against the max and display current voltage, capacity left, etc.

Early prototypes and MVP candidate

In the photos above you can see some of the early design and functional prototypes we did. These were extremely valuable in evaluating basic functionality (are we meeting our design criteria), user experience (can the intended user actually use this thing?), and understanding the limits of our design -- what it can and can't do. After 5 or 6 iterations with electronics, software, packaging, and overall user experience, we settled on our current design and generated our minimally viable product or MVP. Things we left out...for now. One obvious thing we have left out, for now, is the ability to measure other pollutants, such as NOx, SOx, O3, CO, and other criteria gases. One reason is cost. To purchase reasonably accurate and calibratable sensors is cost-prohibitive for this low-cost project. Sure, there are dozens of low cost gaseous monitors available, but most carry huge disclaimers stating "not for quantitative measurement" or "use only in indoor environments". Others tell you that the sensors themselves will only last for a short time before needing replacement of their electrochemical elements.

And, Above All...

"A good scientist is a person with original ideas. A good engineer is a person who makes a design that works with as few original ideas as possible. There are no prima donnas in engineering" - Freeman Dyson

Step 8: Use Cases

There are several use cases envisaged for BackpAQ:

Mobile with Smartphone, Data Transmission via WiFi
Mobile with Smartphone, Data Transmission via mobile hotspot or cellphone
Stationary with Data Transmission via WiFi
Stationary with Data Transmission via hotspot

To keep costs low, it is assumed that BackpAQ will utilize the smartphone's GPS location service. If this service is not available and the BackpAQ is in a fixed location, the user can enter a lat and lon location at config time so that the data is still geolocated.

Step 9: Bill of Materials

KITS

In the near future the BackpAQ Kit can be ordered from BackpAQ Labs. For this project we'll utilize kits made available through Sustainable Silicon Valley. The kit includes all the necessary components needed to build your own BackpAQ. Some benefits of getting the kit: overall lower cost, little soldering is required and the holes on the enclosure are pre-made. The option is also available to purchase the individual components which are listed below)

PARTS

Here's an annotated list of what you'll currently need to build a BackpAQ V2:

Heltec ESP32 Wifi Kit V2 w/built-in .96" OLED and LiPO charger Amazon
Adafruit PMSA003I Air Quality Breakout w/ STEMMA QT AdaFruit
Sensirion SGP-30 TVOC Sensor Amazon or AdaFruit
Sensirion SCD-41 CO2 Sensor Mouser or Digi-Key
Adafruit SPH0645 MEMS Microphone board Adafruit
3.7V 2500 mAh LiPO Battery AdaFruit
Pelican Model 1010 Clear Poly Case B&H B&H Photo
Misc parts kits (jack, switch, screws, standoffs, wire, etc.)

Note: The parts in your kit may vary a bit from those in the photos or parts list. Don't worry...we've tested them and they'll work fine.

SOFTWARE

The software that runs BackpAQ can be downloaded from Github here. Be sure to grab the latest version and the associated config file. You'll also need to utilize, download or update the following open source software packages (current as of 5/1/21):

Arduino IDE V1.8.10 (optional, to compile BackpAQ software)
Blynk Library v0.6.1 and IOS app V 2.26.5 (IOS) or Android app 2.27.19 (Android)
ThingSpeak (Free Web-based Cloud application)

SMARTPHONE

To get the most out of BackpAQ you'll need a companion smartphone. Currently BackpAQ (and underlying Blynk app) requires IOS 9.0 or higher or Android 4.2 or higher.

TOOLS

The following tools are recommended for building the unit: drill, various drill bits, files, Phillips-head screwdriver, hot glue gun and glue stick, soldering iron and solder, and various bits of wire, two-sided tape, and silicone.

Step 10: The Build

Let's get started!

Ok, we're ready to get started building! First, let's lay out all of the parts on a flat, clean work surface. Pro tip: use an egg carton or old-school ice cube tray to organize the very small parts like fasteners, nuts, etc.

Assembly Instructions

The kit comes with a pre-drilled Pelican 1010 clear polycarbonate case and all parts necessary to complete the build. If you choose to order the parts and build yourself, you'll have to do some very basic mechanical and electronics (like soldering a few wires and drilling a few holes) to complete the build. And believe it or not, all of the parts you see in front of you will indeed fit in here! But it's a good idea to follow the suggested assembly sequence in order to fit the lower-level parts first before the one's that go on top. For example we'll want to secure the AMS7003 sensor (that's the small square blue box) in the lower left corner before we install the other components like the battery or temperature sensor. Just follow along and you'll see the logic here.

OK, here's the recommended assembly sequence for the BackpAQ unit. See above photos for placement, and consult schematic for wiring details, and take your time to do it right. Should take an hour or two to complete these steps, depending on where you are starting from. Oh, and one more thing: always verify polarity of power connections before activating your device for the first time (see Step 9). Ok, let's get started!

Locate the clear Pelican case and orient so that the opening tab is at the bottom, facing you. The large holes used for air access and exit will be on your left. All of the steps that follow assume the case is oriented this way.
If you received a BackpAQ kit your case will have pre-drilled holes. If you need to drill the holes yourself, see the diagram above for reference in hole location and suggested drill size. Note that these are approximate sizes and may need to be adjusted based on part availability, especially with the switch and power jack. It is highly recommended that you drill all of the holes first before proceeding to the assembly steps.
Place the blue AMS7003 sensor (it has a double-sided adhesive) to align with the intake and outtake holes. Don't peel adhesive just yet. The sensor inlet and outlet holes may not exactly line up with the holes in the case. Just fit to center on the holes as best you can. Plug in the two QWIIC cables BEFORE ATTACHING the PM sensor as it will be difficult to fit when other parts are installed. Now peel adhesive and stick firmly to bottom of case.
Locate and place the red SGP-30 TVOC sensor board atop the sensor, but don't fasten with adhesive pad yet. Plug the QWIIC cable from the AMS7003 into one end of the SGP-30. Now, using the double-sided adhesive pad, fasten both to the top of the PM sensor so that it lines up with the inlet hole in the top of the case (to the left of the Heltec MCU.) See photos for positioning and alignment.
Next, locate the BME280 temp/humidity sensor. Line it up with with the hole on the bottom-left side of the case and secure with the spacer and M2 screw and nut. Make sure you get the sensor side (small square silver box) facing outward to the hole. Plug the free end of the QWIIC cable into the closest free socket on the SGP-30, in daisy-chain fashion (see photo 1).
Install the LiPO battery (double sided adhesive) to the bottom of the case. Best orientation is vertical, that is, long side along the right-hand side of the case. When done, the LiPO will just fit under the toggle switch. Leave the connector unplugged for now.
Next install the power switch in the provided hole on the lower right-hand side of the case. If the hole is not large enough use the edge of a scissors or blade of a screwdriver to enlarge. Use a small knife blade or other tool to de-burr the hole so that the jack will fit properly. Use pliers or small wrench to tighten the lock washer and nut onto the shaft.
Install the Heltec ESP32 to the top of the case, using the provided adhesive strips on the left and right sides of the display. These are very small and require a bit of close handling to ensure they stick well. Take your time and place carefully in the top lid, aligning with the indicated markers. Locate the small male Heltec power connector and carefully insert into the corresponding socket on the Heltec.
Before doing this step: verify polarity - with a meter - of the red and black wires on the large female power extension as some vendors have supplied us with reversed polarity!!! Now, locate the large female power connector (see photos) and solder the black wire (if verified as positive) to the center or top-most tab on the switch (this may vary as some supplied switches are SPST (2 tabs) and some are SPDT (3 tabs). Circuit works the same with whatever model you have. Now solder the red wire (if verified as negative) to the black wire from the Heltec connector (from Step 7, see photo 1). Insulate the connection with electrical tape of heat shrink tubing.
Next, solder the red wire from the Heltec connector (from Step 7) to the bottom tab on the power switch. Insulate the connection with electrical tape or use the supplied heat shrink tubing to cover neatly.
Install the charging jack as shown in the photos, in the bottom part of the case, right-hand side. Mount yours where the pre-drilled hole is located. If the hole is too small, use a blade screwdriver or scissors to widen the hold as needed. Also, use a small knife blade or other tool to de-burr the hole so that the jack will fit properly. Use pliers or small wrench to tighten the nut onto the shaft.
OK, almost done! Locate the thick black micro USB cable. Solder the red and black wires to their respective solder tabs on the charging jack, as shown in schematic diagram. Pay attention to polarity! It is critical to make sure you have the correct positive and negative connections correct here. This is easy to get wrong...ask me how I know ;-) If in doubt, plug in a 5V-6V source and verify correct polarity with multimeter.
Finally, connect the long 4-wire QWIIC cable to the correct pre-soldered Heltec MCU pins, paying attention to the wire color and pin numbers: red is 3.3V, black is circuit ground, yellow (pin 27) is SDA, and blue (pin 14) is SCL. Plug the other end of the cable into the rightmost QWIIC socket on the AMS7003 board (see photo 1).

Verify all connections (Very important!) and that battery is charged. Turn power on with BackpAQ unit...OLED display should light up with "BackpAQ V2"!

Now that we've verified that our BackpAQ is up and running correctly, we're ready to move on to the software.

Step 11: Software

A Word About the Software and Firmware That Powers BackpAQ

So you've got a working BackpAQ...now what? Sure, you can start monitoring PM and see a little of the data, but you can't really do very much without connecting and configuring the software, or, more correctly, the firmware. Firmware is the computing logic or code that will run on the microcontroller that's running in the BackpAQ unit you just put together.

We've actually done a lot of work for you already; if you have the kit we have pre-flashed the firmware that will help you get up and running quickly. If building from your own parts, you'll need to follow the next few steps to compile and upload the software to your BackpAQ.

To really utilize the full capabilities of your BackpAQ you'll need to do a little configuration of the code. Fortunately, the BackpAQ configuration portal that pops-up when connected to WiFi will allow you do all of the configuration needed to talk to Blynk on your smartphone and Thingspeak on the cloud.

And the best part is that all of the data is saved in the ThingSpeak cloud where you can get at it any time you need to, even data from, say, months ago, to do some powerful analysis and comparisons.

Now let's get the Thingspeak cloud set up so we can get this thing configured.

Step 12: Configuring ThingSpeak - I

Thingspeak

ThingSpeak is an IoT platform that allows users to collect, store and analyze data remotely. It is integrated with MATLAB/MathWorks which helps with data visualizations and analysis. It's where we'll store and manage all of the data collected from the sensor.

Data in Thingspeak are stored within the fields in what are known as channels. Each channel has eight fields. We will be using all of the fields and two channels.

For more information about Thingspeak, refer to the following: ThingSpeak website, ThingSpeak Q&A

Note: students participating in one of our pilot projects will have a pre-provisioned ThingSpeak account. Ask your instructor for details.

Thingspeak Setup

1) First, go to the ThingSpeak website.

2) Click on "Sign Up". A page is opened to create a MathWorks account. Enter credentials and click "Continue". If you already have a MathWorks account click on "Sign In". Note: students participating in one of our pilot projects will have a pre-assigned ThingSpeak account. Ask your instructor for details.

3) An email will be sent for verification. Once confirmed, return to the Thingspeak page and click "Continue"

4) Create a User ID and Password. Check the "Online Services Agreement" box and click "Continue"

5) On the sign-up successful page, click"OK"

6) Finally, there will be a pop-menu asking about the intended usage. Select your option and click "OK"

Step 13: ThingSpeak - II Create ThingSpeak Channels for Your Data

Note: For students participating in one of our pilot studies these Channels have been predefined for you.

1) Select "New Channel" (we'll do this twice)

2a) Fill in description. To keep things in sync with the data the sensors are collecting, we'll need to fill in each field as follows.

For Channel 1:

Enter Name as "BackpAQ Sensor Data I"

Check the box and enter Field 1 as "PM0.1 ug/m3"
Check the box and enter Field 2 as "PM2.5 ug/m3"
Check the box and enter Field 3 as "PM10 ug/m3"
Check the box and enter Field 4 as "Temperature (F)"
Check the box and enter Field 7 as "Longitude (Degrees)"
Check the box and enter Field 8 as "Air Quality Index I"

For Channel 2:

Enter Name as "BackpAQ Sensor Data II"

Check the box and enter Field 1 as "Time stamp"
Check the box and enter Field 2 as "Num of Particles Beyond 0.5 um/.1L"
Check the box and enter Field 3 as "Num of Particles Beyond 1.0 um/.1L"
Check the box and enter Field 4 as "Num of Particles Beyond 2.5 um/.1L"
Check the box and enter Field 5 as "Num of Particles Beyond 5.0 um/.1L"
Check the box and enter Field 6 as "Num of Particles Beyond 10 um/.1L"
Check the box and enter Field 7 as "TVOC"
Check the box and enter Field 8 as "eCO2"

For Channel 3:

Enter Name as "BackpAQ Tracks"

Check the box and enter Field 1 as "Userid"
Check the box and enter Field 2 as "Latitude"
Check the box and enter Field 3 as "Longitude"
Check the box and enter Field 5 as "PM2.5"
Check the box and enter Field 6 as "Track Name"
Check the box and enter Field 7 as "TVOC"
Check the box and enter Field 8 as "Comments"

2b) Click on "Save Channel" for each channel. A dashboard will open with eight charts for each. Each chart can then be edited individually. When you're done, the new channels should resemble the last 3 pics above.

OPTIONAL

3a) Add some numerical or graphical displays to show the PM, particle counts, AQI, temp and humidity readings. To do this select "Add Widgets" then "Numerical Display" and click on "Next". Fill in the required information and click "Create". Repeat this for all of the appropriate fields. There are numerous examples of what can be computed and visualized.

3b) Finally, drag the widgets and place them side by side with the corresponding graphs.

Step 14: Customize BackpAQ and Recompile Code

Note: BackpAQ units come pre-flashed with the latest firmware and configured for use. These instructions may be used to make modifications or enhancements to the code and re-flash the device.

Get Your Info Ready

In order to upload data to ThingSpeak, you'll need your Thingspeak Channel IDs and Write API Keys. Go to your ThingSpeak account. In the "BackpAQ Sensor Data I, II and BackpAQ Tracks" channels, click on "API Keys" and note the "Channel ID" and "Write API Key" for each.

Download Latest BackpAQ Code

To access the latest version of BackpAQ for this specific build, go to Github and download the "Code" to your desktop. You'll need to copy it to the Arduino folders so that the IDE can see it.

Install Libraries

The code for this project makes use of several customized libraries and header files. They need to be added to the Arduino IDE before the code can be used. See 3rd image above for a complete list of the libraries required for BackpAQ V2.0)

To install the necessary libraries for BackpAQ V2, use the Arduino "Manage Libraries" tool:

Tools --> Manage Libraries --> then enter the name of the library you wish to install. It will be located and be ready to install. Click "Install" and it will be automatically copied to your Arduino directory.

That's it! Next step -->

Step 15: Compile and Load BackpAQ Firmware Using Arduino IDE

Note: This is an optional step as most BackpAQ devices come with pre-loaded firmware. If you wish to experiment with the code you can use this procedure to update on your BackpAQ device.

Set up Arduino IDE for your BackpAQ device

1) First we'll need to set up IDE for the BackpAQ hardware we're using, in this case the Heltec ESP32 microcontroller. Go ahead and connect the BackpAQ to the computer through the micro-USB connector on the side.

1a) In the Arduino IDE go to Tools --> and select, for "Board", "Heltec WiFi LoRa 32(V2)". You'll have this board if you have used the Heltec or similar ESP32 chips before. The other fields should then get filled in with the appropriate values for this MCU.

1b) If you don't see the "Heltec WiFi LoRa 32(V2)" board in your Arduino IDE Board list, you'll have to add it. To do this, you can look here to see the exact process you need to follow. Note that this is different from adding libraries to the Library Manager. In this version, we will not be using the Heltec Library. See Picture 2 above for what we want to end up with. Note that you'll need Heltec ESP32 V0.4 for this project.

(2) Now let's connect to the serial port. To see which value to enter for "Port" -- which connects the IDE to your MCU -- you'll need to connect your BackpAQ device to your compute, via the USB port. or, if you know it already, simply enter it here. This will be computer-dependent and will vary across PCs and Macs and IDE versions. For the ESP8266, the port names tend to have unusual names, e.g: On Mac OS: /dev/tty.usb.modem8232, or, on my Mac, in the Arduino IDE, as /dev/cu.SLAB_USBtoUART

On Windows: It might be Com4 or Com3 (you'll have to scan ports to see which one Windows assigned)

On Linux /dev/ttyUSB0 or /dev/ttyACM0 (you Linux types already know this) Typically, the Heltec ESP32 MCU we are using uses the CP2102 USB chip, and may require a driver download depending on what's already on your system. Here is a good reference.

On my Mac the port is known as " /dev/cu.SLAB_USBtoUART ". Your mileage may vary. If your port is not showing up, or you can't communicate with the ESP, you probably need to install USB to UART Bridge VCP drivers. To do so, go here, then download and install the drivers for your operating system. After installing the drivers, restart the Arduino IDE.

(3) Now, compile and upload the code. Messages, as well as sensor data, can be viewed on the serial monitor.

(4) If compile and upload is successful, you can proceed to the BackpAQ setup steps.

If there is an error or you want to monitor the execution for debugging purposes, open the serial monitor by going to Tools -> Serial Monitor or press Ctrl+Shift+M on your keyboard. Set the baud rate to 115200 and select "Carriage return". Data should now be uploading to ThingSpeak. Note: The upload rate is set to every 17 seconds. The adjustment for a longer upload period can be made within the BackpAQ code. However, less than 17 seconds is not recommended due to Thingspeak limits on their API.

Step 16: Install and Configure Blynk

As you may have surmised from the earlier steps, we are using the versatile and easy-to-program Blynk system to run our BackpAQ smartphone app. It's actually very easy to deploy and get running, so let's get started.

Note: If you are participating in one of our BackpAQ pilot projects, a Blynk account will be have provisioned for you.

Here are the three easy steps to get the Blynk platform up and running:

1) Download the Blynk App Blynk app for iOS and Android is the easiest way to build your own mobile app that work with the hardware of your choice. No iOS or Android coding required. It's the base for the BackpAQ app that runs on your smartphone. If you need help with this or another Blynk function, this is a great resource.

Grab the current IOS Blynk app or Andriod Blynk app

Next,

1) Create New Account in Blynk app Account is needed to save your projects and provide access from any smartphone you have. Note: If you are participating in one of our BackpAQ pilot projects, a userid will have been provisioned for you.

2) Create New Project • Click "New Project" and then click on the QR icon in the upper left corner to activate your phone's camera. Link to the current BackpAQ V2 on Github which will locate the current BackpAQ V2 app QR code and files. Now, aim the camera over the displayed QR code to download the BackpAQ app. You will then (typically) see a message telling you that you that "you don't have enough energy". Don't fret...we need energy to power BackpAQ! (Note: if you are participating in an SSV-sponsored project you will have a pre-provisioned BLYNK account and this will be paid for.)

For this BackpAQ about 9000 "energy points" are required, so make sure you have enough. For a new account Blynk gives 2000 free energy points, so you'll have to make up the 7000 point difference. Energy points may be purchased through the Blynk app and subsequently via your Apple App Store or Google Play Store and are a great deal at about $12 for the complete BackpAQ app!

After the project has been created, select "Send Auth Token by Email" and Blynk will send you Auth Token over email. Check your email inbox and find the Auth Token for use in the next step.

Step 17: Configure Your BackpAQ Device

When you first power up your BackpAQ unit, after a few seconds you’ll see the following display on the top of the case:

This is BackpAQ prompting you to connect your WiFi (on your laptop, tablet or phone) to BackpAQ’s own SSID, which is “BackpAQ” + a set of unique hex characters that represent the id of the processor contained within the unit (see first photo above). Next, depending on what kind of device you are using, and what operating system & browser you use, your browser should automatically pop up with the BackpAQ Configuration webpage displayed. If this does not happen automatically with about 5 seconds, just launch your browser manually and go to address 192.168.4.1 and the Configuration page will appear. You will see a page that looks like the second - fourth photos.

Fill in the required fields, scrolling down to complete all. The Blynk token is key if you want to use the BackpAQ app. And be sure to check “mobile” if you intend to use BackpAQ for mobile monitoring, and ignore the “GPS Location” box.

Note: If you want to use BackpAQ as a mobile AQ monitor, you'll need to enter your phone's mobile hotspot SSID and password here.

Once connected and configuration is complete, the device will continue its setup sequence and should look like the image above. Finally, once the sensor has warmed up, you should see something like photo five.

Finally, at photo six you should see the PM readings displayed. If there are no TVOC or CO2 readings check to see if you have that sensor installed. On many devices it is optional, so these readings will be zero.

Step 18: Using BackpAQ

How to Get Started Using BackpAQ

Here is a set of Frequently Asked Questions (FAQs) to get you started. See the companion document, "BackpAQ V2 User's Guide", for more detailed usage.

What do I need to get started with BackpAQ V2?
- BackpAQ battery is fully charged. When done charging the red LED goes out and the green "done charging" LED is lit.
- An Android or Apple smartphone with GPS. See below for specs.
- Access to GitHub to download the BackpAQ app.
- A laptop, tablet or other device with WiFi to configure your BackpAQ device.
- If you intend to record mobile sessions you'll need a cellular or WiFi connection for your smartphone.
- If you plan to record a fixed-WiFi session, you’ll need access to a wireless router with a 2.4 GHz band.
How do I know that BackpAQ is working correctly?

The BackpAQ V2 device has two LEDs. One serves as the battery-charging indicator and the other serves as the connection indicator. The battery-charging indicator is located closest to the USB charging port. When it’s red, the battery is charging and when it turns off the battery is fully charged. The connection indicator is located closest to the power switch.

How do I activate the configuration utility for BackpAQ?

To configure your BackpAQ device a web-based configuration utility is provided. To activate the utility, switch the BackpAQ device on

How do I configure BackpAQ to record and track a mobile session, or act as a fixed monitor?

If you plan on moving around with the BackpAQ while recording air quality measurements, configure the BackpAQ to record a mobile session by selecting the "Mobile" radio button. If you plan to leave the BackpAQ indoors or locate it outside then configure it to record a fixed session by leaving the button unchecked.

When recording a mobile BackpAQ session, measurements are created, timestamped, and geolocated about every 40 seconds. When recording fixed BackpAQ sessions, measurements are created and timestamped about every 40 seconds with location set to coordinates you supply. Enter these - (Latitude, Longitude) - in the configuration dialog.

How does BackpAQ communicate with the cloud, ThingSpeak and the BackpAQ app?

If you are operating BackpAQ in a fixed location, it sends data over WiFi via the 2.4 GHz band of your wireless router. If operating mobile, BackpAQ sends data over WiFi to your smartphone's wireless hotspot, which, in turn, relays the data over the cellular network to ThingSpeak and Blynk servers.

Does BackpAQ save my data in a database?

Yes, in ThingSpeak.com

Once I set up my BackpAQ and connect it to the BackpAQ app, how will I know that it's sending data?

How can I access the data in ThingSpeak?

BackpAQ uses ThingSpeak to store and manage air quality data it observes. ThingSpeak™ is an IoT platform that uses channels to store data sent from apps or devices.

Can I collect data using a smartphone without a cellular data connection?

The BackpAQ app can record the BackpAQ measurements and sync your session data over WiFi without need for a cellular data plan. The only thing that won't work is that the map tiles inside the app won't load when you’re away from WiFi and without a data plan. You don't have to do anything special; just use the app as you normally would. Once you've stepped outside and started recording, make sure the colored dots displayed on the screen create a trail. If the dots are being layed down directly on top of one another you don't have a proper GPS fix as it's not registering your movement.

The WiFi network that my BackpAQ was connected to went down temporarily. Now that the WiFi network is up again, do I need to do anything to get my BackpAQ streaming again?

Once you configure a BackpAQ to record a fixed session, it will send data to the BackpAQ website every minute until you turn it off. You don't need to do anything if the WiFi connection is dropped. Simply restore the WiFi signal and the data will continue streaming.

What smartphones work best with the BackpAQ?

Your smartphone needs to come with GPS and have access to the GitHub website. We also recommend buying Android devices that cost $100 or more because you get what you pay for. The price of an Android device is frequently a better indicator of compatibility with the BackpAQ app than the hardware and software specifications alone because more expensive Android devices are generally better built. If you plan to buy multiple Android devices, buy one device and test thoroughly with the BackpAQ app before buying multiples.

How much data is consumed when sending BackpAQ data over cellular?

Approximately 450 megabytes per month.

How much power is consumed by BackpAQ when it’s plugged in and running?

When powered and running 24/7, BackpAQ consumes less than a nickel’s worth of electricity in a month.

BackpAQ Personal Air Quality Monitor User Guide V0.98.pdf
Download

Step 19: Plantower PMS7003 Specifications

backpaq V2 schematic v0.5.pptx
Download

Step 20: Additional Material on Air Quality Measurements

Impact of CO2 on human decision-making performance

The onset of COVID-19 in 2020 heightened the concern of being exposed to human-exhaled airborne infectious aerosols. In indoor environments, these harmful agents can easily accumulate due to poor air ventilation or contaminated filters from air handling units. To combat this, proper ventilation and exposure to fresh air has become one of the best methods to reduce the risk of infection indoors. The question then becomes, how can building administrators measure the amount of potential airborne infections indoors? Since buildings generally do not have significant internal sources of CO2 without humans occupying them, the presence of CO2 molecules has become a good indicator of how much exhaled breath is accumulating indoors (which in turn also serves as a good surrogate for human-exhaled infectious aerosols).

Sensors like the SCD4x can now play an important role for ventilation systems, as they can accurately determine the levels of airborne viruses indoors and initiate any ventilation needed once CO2 levels exceed a certain risk threshold. The use of such CO2 controlled ventilation systems can also improve energy efficiency, as they are able to optimize the supply of fresh air according to the actual need for outside air as determined by the CO2 sensor.

Health impact

Carbon Dioxide is a contributing factor to the Sick building syndrome (SBS), a medical condition where people in a building suffer from symptoms of illness or feel unwell for no apparent reason. The symptoms tend to increase in severity with the time people spend in the building, and improve over time or even disappear when people are away from the building. The main identifying observation is an increased incidence of complaints of symptoms such as headache, eye, nose, and throat irritation, fatigue, and dizziness and nausea. These symptoms appear to be linked to time spent indoors, though no specific illness or cause can be identified. A 1984 World Health Organization (WHO) report suggested up to 30% of new and remodeled buildings worldwide may be subject of complaints related to poor indoor air quality. In homes and offices: A 100 ppm increase in indoor CO2 concentration was significantly associated with headache (..). Office workers exposed to indoor CO2 concentrations higher than 800 ppm reported a significant increase in eye irritation and upper respiratory symptoms. A 100 ppm increase in dCO2 in the range from 467 to 2800 ppm in indoor CO2 was significantly associated with dry throat, tiredness, and dizziness (417 participants from 87 offices) (Lu et al., 2015). A 100 ppm increase in CO2 concentration (range, 549–1318 ppm) was positively correlated with non-specific symptoms including headache and dizziness (107 participants from 11 offices) although the correlation was not significant (Azuma et al., 2018). Twenty-two participants were exposed to CO2 at 600, 1000, and 2500 ppm (three 2.5-h sessions, one day; artificially elevated CO2 concentrations) in an office-like chamber. Statistically significant decrements occurred in cognitive performance (decision making, problem resolution) starting at 1000 ppm (Satish et al., 2012).

In schools

A study in schoolchildren exposed to indoor CO2 concentrations higher than 1000 ppm showed significantly higher risk for dry cough and rhinitis (654 children of 46 classrooms) but outdoor air flow rate per person was inversely correlated with indoor CO2 concentrations (Simoni et al., 2010). A 200 ppm increase in indoor CO2 concentration (range, 1000– 2000 ppm) in 45 day care centers (DCCs) was significantly associated with reported wheezing in the 3186 attending children, and a positive trend was observed between CO2 concentration and the prevalence of asthma. Source: " Effects of low-level inhalation exposure to carbon dioxide in indoor environments", Web: https://www.sciencedirect.com/science/article/pii...

Introduction: BackpAQ Personal Air Quality Monitor V2